An RTM-Driven Machine Learning Approach for Estimating High-Resolution FAPAR From LANDSAT 5/7/8/9 Surface Reflectance by Guodong Zhang, Gaofei Yin, Yi Zhang, Jiangchuan Hu, Zongyan Li, Changjing Wang, Dujuan Ma, Jiangliu Xie

“…This study synergized the strengths of RTM and machine learning algorithm while overcoming the limitations of RTM parameterization and generalization, providing an efficient and robust Landsat FAPAR estimation approach. …”
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A visual positioning method for tunnel boring machines in underground coal mines based on anchor net features by Xuhui ZHANG, Yunkai CHI, Yuyang DU, Junying JIANG, Wenjuan YANG, Youjun ZHAO, Jicheng WAN, Yanqun WANG, Chenhui TIAN

“…Through illumination adjustment while suppressing noise, images with uniform illumination and clear textures were obtained. …”
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Deep Reinforcement Learning Assisted UAV Path Planning Relying on Cumulative Reward Mode and Region Segmentation by Zhipeng Wang, Soon Xin Ng, Mohammed EI-Hajjar

“…Our proposed region segmentation aims to reduce the probability of DRL agents falling into local optimal trap, while our proposed cumulative reward model takes into account the distance from the node to the destination and the density of obstacles near the node, which solves the problem of sparse training data faced by the DRL algorithms in the path planning task. …”
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Fusion-Based Localization System Integrating UWB, IMU, and Vision by Zhongliang Deng, Haiming Luo, Xiangchuan Gao, Peijia Liu

“…Among them, visual–inertial odometry (VIO)-based techniques are notably limited by lighting conditions, while ultrawideband (UWB)-based algorithms are highly susceptible to environmental interference. …”
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Providing a Robust Dynamic Pricing Model and Comparing It with Static Pricing in Multi-level Supply Chains Using a Game Theory Approach by Sara Mehrjoo, Hanan Amoozad Mahdirji, Jalil Heidary Dahoei, Seyyed Hossein Razavi Haji Agha, Mahnaz Hosseinzadeh

“…For data analysis, a genetic algorithm, particle accumulation optimization, and MATLAB software were employed. …”
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Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization by Miguel García-Ortegón, Srijit Seal, Carl Rasmussen, Andreas Bender, Sergio Bacallado

“…So far, most studies of NPs have focused on low-dimensional datasets of highly-correlated tasks. While these homogeneous datasets are useful for benchmarking, they may not be representative of realistic transfer learning. …”
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Pengembangan Deep Learning untuk Sistem Deteksi Dini Komplikasi Kaki Diabetik Menggunakan Citra Termogram by Medycha Emhandyksa, Indah Soesanti, Rina Susilowati

“…In this study, four deep convolutional neural network models were designed with Occam's razor principle through hyperparameter settings on the algorithm structure aspect in the form of number of layers and optimization aspect in the form of optimizer type. …”
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Deep Clustering of Student Code Strategies Using Multi-View Code Representation (CMVAE) by Zhengting Tang, Shizhou Wang, Liangyu Chen

“…The model captures structural features by transforming code into tree graphs and extracting centrality measures, while CodeBERT provides semantic embeddings. Through a joint optimization of reconstruction loss and clustering loss, the model effectively integrates multiple code representations. …”
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Integrated Waste Management in the Circular Economy Era: Insights from Research and Practice by Charisios Achillas, Christos Vlachokostas

“…Technological advancements, such as AI-driven waste sorting and route optimization algorithms, are highlighted alongside policy frameworks supporting circular economy principles. …”
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Revolutionizing Supply Chain Management With AI: A Path to Efficiency and Sustainability by Kassem Danach, Ali El Dirani, Hassan Rkein

“…Through an in-depth analysis of various AI techniques—such as machine learning, predictive analytics, and optimization algorithms—this study offers novel insights into their applicability in solving complex supply chain problems like demand forecasting, inventory management, and logistics optimization. …”
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Privacy-preserving method for face recognition based on homomorphic encryption. by Zhigang Song, Gong Wang, Wenqin Yang, Yunliang Li, Yinsheng Yu, Zeli Wang, Xianghan Zheng, Yang Yang

“…To overcome this limitation, this paper introduces an optimization scheme based on clustering algorithms to accelerate the facial recognition process within the HE_FaceNet framework. …”
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Perception-Based H.264/AVC Video Coding for Resource-Constrained and Low-Bit-Rate Applications by Lih-Jen Kau, Chin-Kun Tseng, Ming-Xian Lee

“…By targeting regions most relevant to the human visual system, the proposed method enhances perceptual quality while optimizing resource usage, making it particularly suitable for embedded systems and bandwidth-limited communication channels. …”
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A Camera-Embedded Self-Adaptable Finger With Multi-Modal Sensing Capabilities for Robotic Manipulation by Muhammad Usman Khalid, Hafiz Muizz Ahmed Sethi, Nirmal Kumar Ravikumar, Halar Haleem, Alessandro Seitone, Mattia Frascio, Perla Maiolino, Matteo Zoppi

“…Customized rigs integrated with a Universal Testing Machine (UTM) were used for sensor characterization, dataset acquisition, and slip detection parameter optimization. Furthermore, the system was validated through integration with an industrial gripper in an experimental sequence on different object types to mimic real-world manipulation, where both algorithms were integrated and deployed on Raspberry Pi 5 to achieve proprioceptive and exteroceptive sensing. …”
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Optimasi Proses Klasterisasi di MySQL DBMS dengan Mengintegrasikan Algoritme MIC-Kmeans Menggunakan Bahasa SQL dalam Stored Procedure by Issa Arwani

“…Median Initial Centroid (MIC)-Kmeans algorithm is a development of the K-means algorithm that can provide the optimal solution in determining the initial centroid which has an impact on the accuracy and duration of iterations. …”
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A Comprehensive Survey on AI in Counter-Terrorism and Cybersecurity: Challenges and Ethical Dimensions by Ioannis Syllaidopoulos, Klimis S. Ntalianis, Ioannis Salmon

“…This paper provides a comprehensive overview of AI methodologies, such as predictive analytics, Natural Language Processing (NLP), and machine learning architectures (e.g., Support Vector Machines – SVM and Long Short-Term Memory – LSTM), and optimization algorithms (e.g., Particle Swarm Optimization – PSO), assessing their effectiveness in security applications. …”
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Optimasi Algoritma Naive Bayes dengan Diskritisasi K-Means pada Diagnosis Penyakit Jantung by Nafa Fajriati, Budi Prasetiyo

“…This shows that K-means discretization plays a role in optimizing the performance of the Naïve Bayes algorithm to produce better accuracy. …”
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An Efficient and Cost-Effective Vehicle Detection and Tracking System for Collision Avoidance in Foggy Weather by Naeem Raza, Muhammad Asif Habib, H. M. Sajid Imran, Abdul Qayum, Sajida Perveen, Sohail Jabbar, Shahzad Sarwar, Mudassar Ahmad

“…The proposed ECE-VDT system encompasses an optimized SimYOLO-V5s algorithm and its five variants for vehicle detection, while the optimized deep-SORT algorithm is proposed for vehicle tracking. …”
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Enhanced Rapid Autofocus Back-Projection for PBSAR Based on the GEO Satellite by Te Zhao, Jun Wang, Zuhan Cheng, Ziqian Huang, Jiaqi Song

“…Conventional autofocusing algorithms operate under the assumption that measurement errors primarily perturb phase components while exerting negligible influence on signal envelopes. …”
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A Vision-Based Method for Detecting the Position of Stacked Goods in Automated Storage and Retrieval Systems by Chuanjun Chen, Junjie Liu, Haonan Yin, Biqing Huang

“…This paper proposes a novel machine vision-based detection algorithm that integrates a pallet surface object detection network (STEGNet) with a box edge detection algorithm. …”
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MAB-RSP: Data pricing based on Stackelberg game in MCS by Yongjiao Sun, Xueyan Ma, Anrui Han

“…Experiments demonstrate that the algorithm improves revenue while ensuring balanced benefits for all participants.…”
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